Weak AI visibility with 9 of 22 criteria passing. Biggest gap: llms.txt file.
Verdict
coperniq.io shows foundational AEO signals but is currently under-optimized, with an overall score of 37/100. Strengths include Entity Authority & NAP Consistency (8/10), Author & Expert Schema (9/10), and Schema Coverage Depth (7/10), indicating credible identity and usable structured signals. However, critical machine-discovery assets are missing: llms.txt (0/10), FAQ coverage (0/10), RSS/Atom feed (0/10), and list/table extractability (0/10), while freshness and publishing velocity remain weak (2/10 each). The site is visible to crawlers, but not yet formatted for consistent AI answer extraction at scale.
Scoreboard
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Top Opportunities
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Guides for the criteria with the most room for improvement
Tidio has a 251-line llms.txt. Crisp has zero. The score gap: +29 points. This single file tells AI assistants exactly what your site does -and without it, they're guessing.
AI assistants are question-answering machines. When your content is already shaped as questions and answers, you're handing AI a pre-formatted citation. Sites that do this right get extracted -sites that don't get skipped.
Our site runs 87 FAQ items across 9 categories with FAQPage schema on every one. That's not excessive -it's how we hit 88/100. Each Q&A pair is a citation opportunity AI can extract in seconds.
Sitemaps tell crawlers what exists. RSS feeds tell them what changed. If you don't have one, your new content waits days -or weeks -to be discovered.
Want us to improve your score?
We build citation-ready content that AI engines choose as the answer.